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Generating Quality Items Recommendation by Fusing Content based and Collaborative filtering

Recommender systems guides in filtering data to get the relevant information. Commonly used recommendation approaches are content based filtering and collaborative filtering.  ...  In this paper, we have tried to enhance the quality of the items recommendation system by fusing both content based and collaborative filtering uniquely.  ...  ACKNOWLEDGMENT First of all, let me thank the Almighty for his blessing for the completion of my work. Secondly my guide Dr.  ... 
doi:10.35940/ijitee.i1077.0789s19 fatcat:vq2dio3mdnci3mtdyzhytvwj5y

Generating Items Recommendations by Fusing Content and User-Item based Collaborative Filtering

Anand Shanker Tewari
2020 Procedia Computer Science  
The two mainstream recommendation systems are Content Based Filtering (CBF) and Collaborative Filtering (CF).  ...  The two mainstream recommendation systems are Content Based Filtering (CBF) and Collaborative Filtering (CF).  ...  Once the items' profiles are constructed, the PC block uses these items' profiles to construct the users' profiles.  ... 
doi:10.1016/j.procs.2020.03.215 fatcat:vwjgn4gy45dnngn7r3va75thgu

Ontology-Based User Profiling for Personalized Acces to Information within Collaborative Learning System

Mohammed Amine Alimam, Yasyn Elyusufi, Hamid Seghiouer
2014 International Journal of Euro-Mediterranean Studies  
and constructing semantic users' profiles.  ...  The paper is concluded by presenting experiment results, revealing that the use of the subject ontology extension approach satisfyingly contributes to improvement in the accuracy of system recommendations  ...  However, the ontology is used as the reference to construct a user interest profile.  ... 
doaj:35903f37cc714b35b3a5ccab2d346c84 fatcat:cfa2czehifdrrautzwtw6kpju4

A Strategy toward Collaborative Filter Recommended Location Service for Privacy Protection

Peng Wang, Jing Yang, Jianpei Zhang
2018 Sensors  
A new collaborative filtered recommendation strategy was proposed for existing privacy and security issues in location services.  ...  Then, density prioritization was used to choose similar user groups as service request responders and the neighboring users in the chosen groups recommended appropriate location services using a collaborative  ...  Based on the distributed system structure, two different collaborative filtering recommendation algorithms were designed for user position profile and user position information to recommend LBS services  ... 
doi:10.3390/s18051522 pmid:29751670 pmcid:PMC5982126 fatcat:3754czry7zhuzkhagxwbrw7yim

Semantic Learning Service Personalized

Yibo Chen, Chanle Wu, Xiaojun Guo, Jiyan Wu
2012 International Journal of Computational Intelligence Systems  
construct the user social relationship profile, and improved the collaboration filtering algorithm to recommend personalized learning resources for users.  ...  Due to lack of semantic analysis for keywords and exploring the user contexts, the system cannot provide a good learning experiment.  ...  construct the user social relationship profile, and improved the collaboration filtering algorithm to recommend personalized learning resources for users.  ... 
doi:10.1080/18756891.2012.670528 fatcat:k7q675hu7ba53p33lwlc2qh6pu

Location-Aware Personalized News Recommendation Based on Behavior and Popularity Technique

Hengane Shubham
2020 International Journal for Research in Applied Science and Engineering Technology  
This method may want to assemble user profiles greater correctly.  ...  This paper investigates a novel user profile model to express users' preferences from different aspects.  ...  corresponding weight, and the last time the user accessed it. 2) News Profile Construction: As we have seen in user profile construction, news profile model has the same stages.  ... 
doi:10.22214/ijraset.2020.27921 fatcat:arvlxufr6faczfwznrfsvzumr4

Improving electronic customers' profile in recommender systems using data mining techniques

Mohammad Julashokri, Mohammad Fathian, Mohammad Reza Gholamian, Ahmad Mehrbod
2011 Management Science Letters  
Proposed model was endeavored to improve the customer profile in collaborative systems to enhance the recommender system efficiency.  ...  Recommender systems are tools for realization one to one marketing. Recommender systems are systems, which attract, retain, and develop customers.  ...  We constructed customer profile matrix by training set and generated 10 recommendations for each customer.  ... 
doi:10.5267/j.msl.2011.06.011 fatcat:qzzojeop4nan3hlqy62cgxckta

A Hybrid Knowledge-Based and Collaborative Filtering Recommender System Model for Recommending Interventions to Improve Elderly Wellbeing

Aini Khairani Azmi
2020 International Journal of Advanced Trends in Computer Science and Engineering  
A recommender system is an information filtering system that helps users select items that most match their preferences from a vast amount of information available.  ...  The Collaborative Filtering (CF) approach is applied to find similar users based on elderly profiles generated from the result of assessments done to the elderly.  ...  would like to thank the Center of Advanced Computing Technologies (CACT), Fakulti Teknologi Maklumat dan Komunikasi, Universiti Teknikal Malaysia Melaka (UTeM), 76100 Durian Tunggal, Melaka, Malaysia for  ... 
doi:10.30534/ijatcse/2020/71942020 fatcat:2silj4uid5fnpd7bvynklwt5qe

Comparative Study on Modern Approaches of Recommender System

A. Bhanu Prasad, Dr. N. Sambasiva Rao, K. Subba Rao, B Lakshmi
2018 International Journal of Engineering & Technology  
Recommender system is a kind of tool for filtering information and items of user interest. There are large number of different approaches for filtering data and information.  ...  All the modern approaches along with traditional recommender systems are listed and explained with their merits and demerits. Some common challenges are also addressed in this context.  ...  If only users rating information is used in constructing the recommendation, it is called "Memory-based" or "Userbased" collaborative filtering.  ... 
doi:10.14419/ijet.v7i4.6.20237 fatcat:tfefzdenm5h4jmunmfz4vxeh5u

Document Recommender Agent Based on Hybrid Approach

Khalifa Chekima, Chin Kim On, Rayner Alfred, Patricia Anthony
2014 International Journal of Machine Learning and Computing  
The need for a system that can assist in choosing the most relevant papers among the long list of results presented by search engines becomes crucial.  ...  These users might be academicians who are searching for relevant academic papers within their interests.  ...  Due to that, constructing an accurate user profile is vital for both collaborative approach and content-based approach.  ... 
doi:10.7763/ijmlc.2014.v4.404 fatcat:vyvnapklkzbxth4n4h3ck32vh4

MARS: An Agent-Based Recommender System for the Semantic Web [chapter]

Salvatore Garruzzo, Domenico Rosaci, Giuseppe M. L. Sarné
2007 Lecture Notes in Computer Science  
A single profile agent, associated with the user, periodically collects such information coming from the different user's devices to construct a global user profile.  ...  Agent-based Web recommender systems are applications capable to generate useful suggestions for visitors of Web sites.  ...  Consequently, we suppose that, for each user, there should be constructed a different profile for all the devices he uses.  ... 
doi:10.1007/978-3-540-72883-2_14 fatcat:znmbnls3mrbwphomasspnkuxpu

Study of Collaborative Filtering Recommendation Algorithm Scalability Issue

Reena Pagare, Shalmali A. Patil
2013 International Journal of Computer Applications  
Collaborative Filtering technique is the most successful in the recommender systems field. Collaborative filtering creates suggestions for users based on their neighbors preferences.  ...  Recommender systems provide an important response to the information overload problem as it presents users more practical and personalized information services.  ...  Because it constructs offline to make the recommendation system to recommend item for a user within user bearable time which will also reduce the computational time.  ... 
doi:10.5120/11742-7305 fatcat:dll3ctx2qbelnbjslha444nthm

Recommendation Systems for E-Commerce: A Review

Priya S, Mansoor Hussain D
2017 IJARCCE  
Recommendation system is an intelligent system that generates a ranked list of items on which a user might be interested.  ...  three recommendation system.Thus these recommendation systems have offered many methods for searching and filtering information.Recommender system are rapidly becoming a important tool in E-commerce on  ...  All content based recommender systems has few similar thingslike description of items, user profiles and techniques to compare profile to items to identify which is the required recommendation for a particular  ... 
doi:10.17148/ijarcce.2017.6496 fatcat:657sncidxrcezfoczizqpdj5ye

A Survey Of Recommendation System

K. Surati Alpesh
2018 Zenodo  
Recommendations techniques can be classified in to three major categories: Collaborative Filtering, Content Based and Hybrid Recommendations.  ...  Main objective of this paper is to show various challenges regarding to the techniques that are being used for generating recommendations.  ...  All content based recommender systems has few things in common like means for description of items, user profiles and techniques to compare profile to items to identify what is the most suitable recommendation  ... 
doi:10.5281/zenodo.1253471 fatcat:j4i3mbuqmfdetkqn2o2rfddrcy

An Effective Cold Start Recommendaton Method Using A Web Of Trust

Yu-Hao Wan, Chien Chin Chen
2011 Pacific Asia Conference on Information Systems  
Recommending useful information for new users generally creates a sense of belonging and loyalty, and encourages them to visit e-commerce systems frequently.  ...  The suggestions of those users are then aggregated to provide useful recommendations for cold start users.  ...  Acknowledgements The authors would like to thank the anonymous reviewers for their valuable comments and suggestions. This work was supported in part by NSC 99-2221-E-002-182.  ... 
dblp:conf/pacis/WanC11 fatcat:ayk7ntxexbairn2w3iidk3tiga
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